PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT ?item ?gndId ?subjectName ?sharedIdentifier WHERE {
  ?item p:P227 ?gndStatement .
  ?gndStatement ps:P227 ?gndId .
  ?gndStatement pq:P1810 ?subjectName .
  ?gndStatement pq:P4070 ?sharedIdentifier .
}

The SPARQL query successfully retrieves items with GND IDs, along with their subject names and shared identifiers, where the GND ID statement includes both a subject name qualifier and a shared identifier qualifier.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the items with GND IDs, along with their subject names, and shared identifiers, where the GND ID statement includes both a subject named as qualifier and an identifier shared with qualifier?

[Assistant]
To construct a SPARQL query that answers the user's question, we need to identify the following elements:
1. Items that have a GND ID.
2. The subject names associated with these GND IDs.
3. Shared identifiers that are also part of the GND ID statement.

Let's break down the steps:

1. **Identify the GND ID property**: We need to find the property that represents the GND ID in Wikidata.
2. **Identify the subject name qualifier**: We need to find the property that represents the subject name qualifier in the GND ID statement.
3. **Identify the shared identifier qualifier**: We need to find the property that represents the shared identifier qualifier in the GND ID statement.

### Step 1: Identify the GND ID property
We will search for the property related to GND ID.

[Tool]
Top 10 property alternatives:
1. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier from an international authority file of names, subjects, and organizations
2. The Living New Deal ID, also known as Living New Deal ID, Living New Deal site ID, LND ID (wd:P8567 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a site on the Living New Deal website
3. DDB person (GND) ID, also known as DDB ID, DDB person ID (wd:P13049 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a person in the Deutsche Digitale Bibliothek (DDB); identifier same as the person's GND ID, GND ID
4. Global Terrorism Database ID, also known as GTD ID (wd:P4089 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier in the Global Terrorism Database by the National Cons...um for the Study of Terrorism and Responses to Terrorism (START)
5. Geographical Names Board of NSW ID, also known as Geographical Name Register of New South Wales, NSW GNR, GNR of NSW, GNB NSW ID, Geographical Names Board of New South Wales ID (wd:P3517 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): historical identifier of a geographical feature on a retired Geographical Names Board of New South Wales website
6. Store norske leksikon (Great Norwegian Encyclopedia) ID, also known as GNE ID, Snl ID, SNL ID, Store norske leksikon ID (wd:P4342 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier of an article in the online encyclopedia snl.no
7. Arabic Literary Terms and Devices ID, also known as ADLTD ID, Literary Terms and Devices Dictionary (Arabic) ID, DALTD ID, Dictionary of Arabic Literary Terms and Devices ID (wd:P12658 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a subject page in the Dictionary of Arabic Literary Terms and Devices
8. Green's Dictionary of Slang ID, also known as GDoS ID, Green Dictionary of Slang ID, Green Slang Dictionary ID, Green's Slang Dictionary ID (wd:P11481 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for an entry in the online edition of Green's English slang dictionary
9. Game World Navigator ID, also known as GWN ID, Navigator igrovogo mira ID, NIM ID, nim.ru ID (wd:P10383 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier of a video game on the Game World Navigator website
10. GARD rare disease ID, also known as GARD ID, Genetic and Rare Diseases Information Center ID (wd:P4317 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a rare disease in the United States National Inst...h's Genetic and Rare Diseases (GARD) Information Center database

[Assistant]
The top result for the GND ID property is `wd:P227`. This property represents the GND ID in Wikidata.

### Step 2: Identify the subject name qualifier
We need to find the property that represents the subject name qualifier in the GND ID statement. Let's search for properties related to "subject name".

[Tool]
Top 10 property alternatives:
1. subject named as, also known as established as, established form, established heading, named as, spelled as (wd:P1810 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): name by which a subject is recorded in a database, mentioned as a contributor of a work, or is referred to in a particular context, name
2. applies to name of subject, also known as applies to subject's name, for the name, involved name, limited to the name, valid for the name (wd:P5168 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): (qualifier) label or alias name to which the claim applies (subj...er to name of the value, use "applies to name of object" (P8338), subject named as
3. subject lexeme form, also known as subject form, form demonstrated, applies to form, demonstrates form (wd:P5830 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): (qualifier) statement applies only to listed lexeme forms of statement's subject
4. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): primary topic of a work (see also P180: depicts), depicts
5. academic major, also known as academic subject, college major, field of study, major, studied (wd:P812 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): major someone studied at college/university
6. depicts, also known as portrays, presents, preserves, quotes, represents (wd:P180 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): entity visually depicted in an image, literarily described in a ...o an audiovisual or other medium; see also P921,  'main subject', has part(s)
7. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): specialization of a person or organization; see P106 for the occupation, interested in
8. statement is subject of, also known as statement is the subject of, subject of the statement, subject of the claim, subject of, related item of statement (wd:P805 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): (qualifying) item that describes the relation identified in this statement
9. Open Library subject ID, also known as OL subject ID, OpenLibrary subject ID (wd:P3847 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a topic in the Open Library database
10. facet of, also known as subitem of, topic of, subtopic of, subject in, section in (wd:P1269 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): topic of which this item is an aspect; item that offers a broader perspective on the same topic

[Assistant]
The property `wd:P1810` (subject named as) seems to be the most relevant for representing the subject name qualifier in the GND ID statement.

### Step 3: Identify the shared identifier qualifier
We need to find the property that represents the shared identifier qualifier in the GND ID statement. Let's search for properties related to "shared identifier".

[Tool]
Top 10 property alternatives:
1. identifier shared with, also known as shares identifier with, shares ID with, shared with, shared ID, ID shared with (wd:P4070 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): qualifier, to be used on external identifier IDs, indicating another Wikidata item is also matched to this ID, together with
2. number of records, also known as entries, rows, records, quantitiy of records, number of rows (wd:P4876 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): number of values of an identifier or records in a catalog
3. identifies, also known as uniquely determines, is unique key for, is primary key for, is identifier of, identifier of (wd:P10476 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): this item uniquely and purposefully distinguishes instances of this class from each other
4. Formal Public Identifier (wd:P4506 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): string that identifies uniquely an item using a Formal Public Identifier according to the ISO/IEC 9070:1991 standard
5. inventory number, also known as control number, shelfmark, reference number, reference, object number (wd:P217 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a physical object or a set of physical objects in a collection
6. issued by, also known as issuing body, issuing agent, issuer, identifier issuing body, identifier issued by (wd:P2378 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): organisation or other agent that issues or allocates an identifier, code, classification number, etc.
7. MAC Address Block Large ID, also known as OUI, Organizationally Unique Identifier, MA-L ID, MA-L, MAC Address Block Large ID (wd:P4776 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): unique identifier of an organisation registered with the IEEE
8. Universal Content Identifier, also known as UCI (wd:P11151 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): South Korean national digital content identifier
9. Libraries Australia ID, also known as CNLKIN, NLA Kinetica Service identifier, NLA (Australia) identifier, NLA (Australia) ID, Libraries Australia identifier (wd:P409 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier issued by the National Library of Australia (see also...F component. Format: 1-12 digits, removing leading zero-padding.
10. Google+ ID (archived), also known as Google Plus ID, plus.google.com/, https://plus.google.com/, Google+ username, Google Plus username (wd:P2847 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): Google Plus, account identifier of this person or organization: either starting with a "+" or consisting of 21 digits, website username or ID

[Assistant]
The property `wd:P4070` (identifier shared with) seems to be the most relevant for representing the shared identifier qualifier in the GND ID statement.

### Step 4: Construct the SPARQL Query
Now that we have identified the necessary properties, we can construct the SPARQL query to find the items with GND IDs, along with their subject names and shared identifiers, where the GND ID statement includes both a subject name qualifier and a shared identifier qualifier.

Here is the SPARQL query:

```sparql
SELECT ?item ?gndId ?subjectName ?sharedIdentifier
WHERE {
  ?item p:P227 ?gndStatement.
  ?gndStatement ps:P227 ?gndId.
  ?gndStatement pq:P1810 ?subjectName.
  ?gndStatement pq:P4070 ?sharedIdentifier.
}
```

This query selects the items (`?item`), their GND IDs (`?gndId`), the subject names (`?subjectName`), and the shared identifiers (`?sharedIdentifier`) from the GND ID statements that include both a subject name qualifier and a shared identifier qualifier.

Let's execute this query to see the results.

[Tool]
Got 173 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?item                                   | ?gndId     | ?subjectName             | ?sharedIdentifier                    |
| --------------------------------------- | ---------- | ------------------------ | ------------------------------------ |
| bulla (wd:Q1004230)                     | 4146911-2  | Bulle <Urkunde>          | papal bull (wd:Q189867)              |
| Butterbrot (wd:Q1018075)                | 4005402-0  | Belegtes Brot            | wd:Q111907435                        |
| special education teacher (wd:Q1030095) | 7548137-6  | Sonderpädagogin          | remedial teacher (wd:Q16062258)      |
| special education teacher (wd:Q1030095) | 4181803-9  | Sonderpädagoge           | remedial teacher (wd:Q16062258)      |
| pommer (wd:Q1048934)                    | 4348955-2  | Bomhart                  | pommer (wd:Q540887)                  |
| ...                                     | ...        | ...                      | ...                                  |
| processional parade (wd:Q898830)        | 4176065-7  | Prozession               | religious procession (wd:Q115665045) |
| Order of Friars Minor (wd:Q913972)      | 1008636-5  | Franziskaner             | Franciscans (wd:Q165005)             |
| wd:Q98278107                            | 1170081940 | Schwarz- und Schönfärber | wd:Q98278111                         |
| wd:Q98278111                            | 1170081940 | Schwarz- und Schönfärber | wd:Q98278107                         |
| Aarmühle (wd:Q99437640)                 | 4027269-2  | Interlaken               | Interlaken (wd:Q68103)               |

[Assistant]
The SPARQL query has successfully returned the items with GND IDs, along with their subject names and shared identifiers, where the GND ID statement includes both a subject name qualifier and a shared identifier qualifier.

Here is the final SPARQL query and the answer to the user's question:

```sparql
SELECT ?item ?gndId ?subjectName ?sharedIdentifier
WHERE {
  ?item p:P227 ?gndStatement.
  ?gndStatement ps:P227 ?gndId.
  ?gndStatement pq:P1810 ?subjectName.
  ?gndStatement pq:P4070 ?sharedIdentifier.
}
```

The query returns the following columns:
- `?item`: The Wikidata item.
- `?gndId`: The GND ID of the item.
- `?subjectName`: The subject name associated with the GND ID.
- `?sharedIdentifier`: The shared identifier associated with the GND ID.

The results show that the query is working correctly and returning the expected data.

Let's finalize the answer.

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT ?object ?part ?elevation1 ?elevation2 WHERE {
  ?object p:P2044 ?statement1 .
  ?statement1 ps:P2044 ?elevation1 .
  OPTIONAL {
    ?statement1 pq:P518 ?part .
  }
  ?object p:P2044 ?statement2 .
  ?statement2 ps:P2044 ?elevation2 .
  FILTER ( ?statement1 != ?statement2 ) FILTER ( ?elevation1 < ?elevation2 ) FILTER ( ABS( ?elevation1 - ?elevation2 ) > 500 )
}

The query returns objects that have two statements of elevation above sea level with a difference of more than 500 meters between the two statements, along with the specific part to which the elevation applies (if available) and the elevation values for both statements.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which objects have two statements of elevation above sea level with a difference of more than 500 meters between the two statements? For each object, please include the specific part to which the elevation applies (if available) and the elevation (in meters) for both elevation statements.

[Assistant]
To answer this question, we need to identify objects that have multiple statements for the property "elevation above sea level" (P2044). We also need to filter these objects to only those where the difference between the two elevations is greater than 500 meters. Additionally, we should include the specific part to which the elevation applies, if available.

Let's start by identifying the property for "elevation above sea level" and then build the SPARQL query step by step.

### Step 1: Identify the Property for Elevation Above Sea Level
First, let's confirm the property for "elevation above sea level" in Wikidata.

```json

[Tool]
Top 10 property alternatives:
1. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): height of the item (geographical object) as measured relative to sea level
2. clearance, also known as span height, height of deck bottom, bridge height, height above water, height above valley floor (wd:P2793 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): distance between surface under bridge and bottom of a bridge deck
3. highest point, also known as tallest point, zenith, summit, pinnacle, highest peak (wd:P610 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): point with highest elevation in a region or path, has part(s)
4. maximum operating altitude, also known as ceiling, maximum altitude, service ceiling (wd:P2254 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): ceiling or maximum density altitude at which an aircraft can operate, elevation above sea level
5. floors above ground, also known as floor count, stories, storeys, number of floors, levels above ground (wd:P1101 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): above ground floor count of a building (ground floor and attic included)
6. height, also known as heighth, size, depth over terrain (wd:P2048 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): vertical length of an entity, length
7. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
8. aerial view, also known as overhead view, sky view, orthophotograph, orthophoto, aerial image (wd:P8592 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): image of the subject taken from the air, video, image
9. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
10. cumulative elevation gain (wd:P7297 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): measure of the difference in height between two points on the terrain, when following a track

[Assistant]
The property for "elevation above sea level" is `wd:P2044`.

### Step 2: Build the Initial SPARQL Query
We will start by writing a basic SPARQL query to find objects that have at least two statements for the property `wd:P2044`. We will then filter these objects to only those where the difference between the two elevations is greater than 500 meters.

### Step 3: Refine the Query
We will include the specific part to which the elevation applies, if available, and the elevation values for both statements.

Here is the initial SPARQL query:

```sparql
SELECT ?object ?part ?elevation1 ?elevation2
WHERE {
  ?object p:P2044 ?statement1 .
  ?statement1 ps:P2044 ?elevation1 .
  OPTIONAL { ?statement1 pq:P518 ?part . }

  ?object p:P2044 ?statement2 .
  ?statement2 ps:P2044 ?elevation2 .
  FILTER(?statement1 != ?statement2)

  FILTER(ABS(?elevation1 - ?elevation2) > 500)
}
```

Let's execute this query to see if it returns the expected results.

```json

[Tool]
Got 20,115 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?object                                | ?part | ?elevation1 | ?elevation2 |
| -------------------------------------- | ----- | ----------- | ----------- |
| Saint-Frézal-de-Ventalon (wd:Q1002048) |       | 378         | 1128        |
| Saint-Frézal-de-Ventalon (wd:Q1002048) |       | 1128        | 378         |
| L'Escarène (wd:Q1002059)               |       | 220         | 1054        |
| L'Escarène (wd:Q1002059)               |       | 1054        | 220         |
| LeChee Rock (wd:Q100206221)            |       | 5896        | 1797        |
| ...                                    | ...   | ...         | ...         |
| Kamen (wd:Q999585)                     |       | 4579        | 3283        |
| Buckskin Gulch (wd:Q999908)            |       | 1284        | 4213        |
| Buckskin Gulch (wd:Q999908)            |       | 4213        | 1284        |
| Goldendale (wd:Q999955)                |       | 1637        | 499         |
| Goldendale (wd:Q999955)                |       | 499         | 1637        |

[Assistant]
The query has returned the expected results, listing objects with two different elevation statements where the difference is greater than 500 meters. However, we can see that some objects are listed twice with the same elevations but in reverse order. To avoid this, we can add a condition to ensure that `?elevation1` is always less than `?elevation2`.

Let's refine the query to include this condition:

```sparql
SELECT ?object ?part ?elevation1 ?elevation2
WHERE {
  ?object p:P2044 ?statement1 .
  ?statement1 ps:P2044 ?elevation1 .
  OPTIONAL { ?statement1 pq:P518 ?part . }

  ?object p:P2044 ?statement2 .
  ?statement2 ps:P2044 ?elevation2 .
  FILTER(?statement1 != ?statement2)

  FILTER(?elevation1 < ?elevation2)
  FILTER(ABS(?elevation1 - ?elevation2) > 500)
}
```

Let's execute this refined query to see if it eliminates the duplicate entries.

```json

[Tool]
Got 10,056 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?object                                            | ?part                     | ?elevation1 | ?elevation2 |
| -------------------------------------------------- | ------------------------- | ----------- | ----------- |
| Saint-Frézal-de-Ventalon (wd:Q1002048)             |                           | 378         | 1128        |
| L'Escarène (wd:Q1002059)                           |                           | 220         | 1054        |
| LeChee Rock (wd:Q100206221)                        |                           | 1797        | 5896        |
| Hures-la-Parade (wd:Q1002086)                      |                           | 501         | 1204        |
| Saint-Germain-de-Calberte (wd:Q1002117)            |                           | 275         | 1147        |
| ...                                                | ...                       | ...         | ...         |
| South Fork Lincoln Creek (wd:Q99591224)            | river mouth (wd:Q1233637) | 62          | 645         |
| Funiculaire de Saint-Hilaire du Touvet (wd:Q99601) | beginning (wd:Q529711)    | 260         | 960         |
| Kamen (wd:Q999585)                                 |                           | 3283        | 4579        |
| Buckskin Gulch (wd:Q999908)                        |                           | 1284        | 4213        |
| Goldendale (wd:Q999955)                            |                           | 499         | 1637        |

[Assistant]
The refined query has successfully eliminated the duplicate entries and returned the expected results. Each object is now listed only once with the two different elevation statements where the difference is greater than 500 meters.

### Final Answer
Here is the final SPARQL query and the answer to the user's question:

```sparql
SELECT ?object ?part ?elevation1 ?elevation2
WHERE {
  ?object p:P2044 ?statement1 .
  ?statement1 ps:P2044 ?elevation1 .
  OPTIONAL { ?statement1 pq:P518 ?part . }

  ?object p:P2044 ?statement2 .
  ?statement2 ps:P2044 ?elevation2 .
  FILTER(?statement1 != ?statement2)

  FILTER(?elevation1 < ?elevation2)
  FILTER(ABS(?elevation1 - ?elevation2) > 500)
}
```

This query returns objects that have two statements of elevation above sea level with a difference of more than 500 meters between the two statements, along with the specific part to which the elevation applies (if available) and the elevation values for both statements.

```json

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?work ?author ?title ?subtitle ?publicationVenue ?publisher ?placeOfPublication ?publicationYear WHERE {
  ?work p:P655 ?statement .
  ?statement ps:P655 wd:Q92759384 .
  OPTIONAL {
    ?work wdt:P50 ?author .
  }
  OPTIONAL {
    ?work rdfs:label ?title .
    FILTER ( LANG( ?title ) = 'en' )
  }
  OPTIONAL {
    ?work wdt:P1479 ?subtitle .
    FILTER ( LANG( ?subtitle ) = 'en' )
  }
  OPTIONAL {
    ?work wdt:P1433 ?publicationVenue .
  }
  OPTIONAL {
    ?work wdt:P123 ?publisher .
  }
  OPTIONAL {
    ?work wdt:P291 ?placeOfPublication .
  }
  OPTIONAL {
    ?work wdt:P577 ?publicationYear .
  }
}

The works translated by Gabriele Sprigath, along with the requested information, are as follows:

1. **Work**: Contradiction and Overdetermination (within the German 2011-edition of "For Marx") (wd:Q92772466)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Title**: "Contradiction and Overdetermination (within the German 2011-edition of "For Marx")"
   - **Publication Venue**: For Marx (wd:Q56628039)
   - **Publication Year**: 2011

2. **Work**: For Marx (German edition, 1968) (wd:Q92778414)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Publication Venue**: For Marx (German edition, 1968) (wd:Q92775454)
   - **Publication Year**: 1968

3. **Work**: (wd:Q92790094)
   - **Author**: Louis Althusser (wd:Q184169)

4. **Work**: (wd:Q92790565)
   - **Author**: Louis Althusser (wd:Q184169)

5. **Work**: Marxism and Humanism (within the German 2011-edition of "For Marx") (wd:Q92974962)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Title**: "Marxism and Humanism (within the German 2011-edition of "For Marx")"
   - **Publication Venue**: For Marx (wd:Q56628039)
   - **Publication Year**: 2011

6. **Work**: For Marx (German edition, 1968) (wd:Q93087090)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Publication Venue**: For Marx (German edition, 1968) (wd:Q92775454)
   - **Publication Year**: 1968

7. **Work**: Philosophy as a Revolutionary Weapon (German translation, 2011) (wd:Q93093336)
   - **Title**: Philosophy as a Revolutionary Weapon (German translation, 2011)
   - **Publication Venue**: For Marx (wd:Q56628039)
   - **Publication Year**: 2011

8. **Work**: Philosophy as a Revolutionary Weapon (German translation, 1968) (wd:Q93094446)
   - **Title**: Philosophy as a Revolutionary Weapon (German translation, 1968)
   - **Publication Venue**: For Marx (German edition, 1968) (wd:Q92775454)
   - **Publication Year**: 1968

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which works were tranlated by Gabriele Sprigath? For each work, return the author (if available), title (if available), subtitle (if available), publication venue, publisher, place of publication, and publication year.

[Assistant]
To answer this question, we need to identify the translator Gabriele Sprigath and then find the works translated by her. We also need to gather additional information about these works such as the author, title, subtitle, publication venue, publisher, place of publication, and publication year.

Let's start by searching for Gabriele Sprigath in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Gabriele Sprigath (wd:Q92759384): art historian (*1940, Eisleben [Germany]), art historian, translator
2. Gabriele (wd:Q64528581): name: given and family name
3. Gabriele (wd:Q18429813): human settlement in Italy
4. Gabriele Wittek, also known as Gabriele, Gabriele Maden (wd:Q120030): author and prophet, prophet, author, seer
5. Gabrielė (wd:Q22665995): female given name
6. Gabriele, also known as Gabriele (first name), Gabriele (given name) (wd:Q17765518): female given name
7. Gabriele (wd:Q26780667): family name
8. Hille Oldendorff, also known as Gabriele, IMO 5150678 (wd:Q107067138): ship built in 1956
9. Gabriele Rockenbach, also known as Gabriele (wd:Q57448797): researcher
10. Gabriele (wd:Q108480069): Roman Catholic bishop, Catholic priest, Catholic bishop

[Assistant] The top result for Gabriele Sprigath is `wd:Q92759384`. Let's confirm that this is the correct entity by listing the triples associated with it.

[Tool]
Got 181 rows and 3 columns, showing the first 10 rows below:
| subject                          | property                                        | object                                                                                |
| -------------------------------- | ----------------------------------------------- | ------------------------------------------------------------------------------------------------------ |
| Gabriele Sprigath (wd:Q92759384) | instance of (wdt:P31)                           | human (wd:Q5)                                                                                |
| Gabriele Sprigath (wd:Q92759384) | occupation (wdt:P106)                           | translator (wd:Q333634)                                                                                |
| Gabriele Sprigath (wd:Q92759384) | sex or gender (wdt:P21)                         | female (wd:Q6581072)                                                                                |
| Gabriele Sprigath (wd:Q92759384) | given name (wdt:P735)                           | Gabriele (wd:Q17765518)                                                                                |
| Gabriele Sprigath (wd:Q92759384) | date of birth (wdt:P569)                        | 1940-01-01T00:00:00Z                                                                                |
| Gabriele Sprigath (wd:Q92759384) | family name (wdt:P734)                          | Sprigath (wd:Q92761730)                                                                                |
| Gabriele Sprigath (wd:Q92759384) | place of birth (wdt:P19)                        | Eisleben (wd:Q484870)                                                                                |
| Gabriele Sprigath (wd:Q92759384) | languages spoken, written or signed (wdt:P1412) | German (wd:Q188)                                                                                |
| Gabriele Sprigath (wd:Q92759384) | described by source (wdt:P1343)                 | wd:Q92764963                                                                                |
| Gabriele Sprigath (wd:Q92759384) | official website (wdt:P856)                     | <https://www.philosophie.uni-muenchen.de/lehreinheiten/geistesgeschichte/personen/sprigath/index.html> |
| ...                              | ...                                             | ...                                                                                |

[Assistant]
The entity `wd:Q92759384` is indeed Gabriele Sprigath, and she is listed as a translator. Now, let's find the works translated by her. We will look for works where Gabriele Sprigath is listed as a translator.

We will use the property `P655` (translator) to find the works translated by Gabriele Sprigath. Then, we will gather the required information about these works.

Let's start by finding the works translated by Gabriele Sprigath.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that there are no direct translations linked to Gabriele Sprigath using the `P655` (translator) property. This could be because the works are not directly linked to her as a translator, or the data might be structured differently.

Let's try another approach. We will search for works where Gabriele Sprigath is mentioned as a translator in the statements. We will use the `ps:P655` and `pq:P655` properties to find the works and their details.

Let's execute a more detailed query to find the works translated by Gabriele Sprigath and gather the required information.

[Tool]
Got 8 rows and 8 columns:
| ?work                                                                              | ?author                      | ?title                                                              | ?subtitle | ?publicationVenue                              | ?publisher | ?placeOfPublication | ?publicationYear     |
| ---------------------------------------------------------------------------------- | ---------------------------- | ------------------------------------------------------------------- | --------- | ---------------------------------------------- | ---------- | ------------------- | -------------------- |
| Contradiction and Overdeterminat...rman 2011-edition of "For Marx") (wd:Q92772466) | Louis Althusser (wd:Q184169) | "Contradiction and Overdetermina... 2011-edition of "For Marx")"@en |           | For Marx (wd:Q56628039)                        |            |                     | 2011-01-01T00:00:00Z |
| wd:Q92778414                                                                       | Louis Althusser (wd:Q184169) |                                                                     |           | For Marx (German edition, 1968) (wd:Q92775454) |            |                     | 1968-01-01T00:00:00Z |
| wd:Q92790094                                                                       | Louis Althusser (wd:Q184169) |                                                                     |           |                                                |            |                     |                      |
| wd:Q92790565                                                                       | Louis Althusser (wd:Q184169) |                                                                     |           |                                                |            |                     |                      |
| Marxism and Humanism (within the German 2011-edition of "For Marx") (wd:Q92974962) | Louis Althusser (wd:Q184169) | "Marxism and Humanism (within th... 2011-edition of "For Marx")"@en |           | For Marx (wd:Q56628039)                        |            |                     | 2011-01-01T00:00:00Z |
| wd:Q93087090                                                                       | Louis Althusser (wd:Q184169) |                                                                     |           | For Marx (German edition, 1968) (wd:Q92775454) |            |                     | 1968-01-01T00:00:00Z |
| Philosophy as a Revolutionary Weapon (German translation, 2011) (wd:Q93093336)     |                              | Philosophy as a Revolutionary Weapon (German translation, 2011)     |           | For Marx (wd:Q56628039)                        |            |                     | 2011-01-01T00:00:00Z |
| Philosophy as a Revolutionary Weapon (German translation, 1968) (wd:Q93094446)     |                              | Philosophy as a Revolutionary Weapon (German translation, 1968)     |           | For Marx (German edition, 1968) (wd:Q92775454) |            |                     | 1968-01-01T00:00:00Z |

[Assistant]
The query has returned several works translated by Gabriele Sprigath, along with the requested information. Here is the final SPARQL query and the answer to the user's question:

### Final SPARQL Query
```sparql
SELECT ?work ?author ?title ?subtitle ?publicationVenue ?publisher ?placeOfPublication ?publicationYear
WHERE {
  ?work p:P655 ?statement .
  ?statement ps:P655 wd:Q92759384 .
  OPTIONAL { ?work wdt:P50 ?author . }
  OPTIONAL { ?work rdfs:label ?title . FILTER(LANG(?title) = 'en') }
  OPTIONAL { ?work wdt:P1479 ?subtitle . FILTER(LANG(?subtitle) = 'en') }
  OPTIONAL { ?work wdt:P1433 ?publicationVenue . }
  OPTIONAL { ?work wdt:P123 ?publisher . }
  OPTIONAL { ?work wdt:P291 ?placeOfPublication . }
  OPTIONAL { ?work wdt:P577 ?publicationYear . }
}
```

### Answer
The works translated by Gabriele Sprigath, along with the requested information, are as follows:

1. **Work**: Contradiction and Overdetermination (within the German 2011-edition of "For Marx") (wd:Q92772466)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Title**: "Contradiction and Overdetermination (within the German 2011-edition of "For Marx")"
   - **Publication Venue**: For Marx (wd:Q56628039)
   - **Publication Year**: 2011

2. **Work**: For Marx (German edition, 1968) (wd:Q92778414)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Publication Venue**: For Marx (German edition, 1968) (wd:Q92775454)
   - **Publication Year**: 1968

3. **Work**: (wd:Q92790094)
   - **Author**: Louis Althusser (wd:Q184169)

4. **Work**: (wd:Q92790565)
   - **Author**: Louis Althusser (wd:Q184169)

5. **Work**: Marxism and Humanism (within the German 2011-edition of "For Marx") (wd:Q92974962)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Title**: "Marxism and Humanism (within the German 2011-edition of "For Marx")"
   - **Publication Venue**: For Marx (wd:Q56628039)
   - **Publication Year**: 2011

6. **Work**: For Marx (German edition, 1968) (wd:Q93087090)
   - **Author**: Louis Althusser (wd:Q184169)
   - **Publication Venue**: For Marx (German edition, 1968) (wd:Q92775454)
   - **Publication Year**: 1968

7. **Work**: Philosophy as a Revolutionary Weapon (German translation, 2011) (wd:Q93093336)
   - **Title**: Philosophy as a Revolutionary Weapon (German translation, 2011)
   - **Publication Venue**: For Marx (wd:Q56628039)
   - **Publication Year**: 2011

8. **Work**: Philosophy as a Revolutionary Weapon (German translation, 1968) (wd:Q93094446)
   - **Title**: Philosophy as a Revolutionary Weapon (German translation, 1968)
   - **Publication Venue**: For Marx (German edition, 1968) (wd:Q92775454)
   - **Publication Year**: 1968

Now, let's provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?place ?placeLabel ?instanceOf ?partOf WHERE {
  ?place wdt:P37 wd:Q9027 .
  ?place wdt:P31 ?instanceOf .
  ?place rdfs:label ?placeLabel .
  OPTIONAL {
    ?place wdt:P361 ?partOf .
    ?partOf rdfs:label ?partOfLabel .
    FILTER ( LANG( ?partOfLabel ) = 'en' )
  }
  FILTER ( ?instanceOf = wd:Q515 || ?instanceOf = wd:Q15284 ) FILTER ( LANG( ?placeLabel ) = 'en' )
}
ORDER BY ?placeLabel

Got 9 rows and 4 columns:
| ?place               | ?placeLabel | ?instanceOf    | ?partOf                                      |
| -------------------- | ----------- | -------------- | -------------------------------------------- |
| Espoo (wd:Q47034)    | Espoo       | city (wd:Q515) | Helsinki capital region (wd:Q18691387)       |
| Espoo (wd:Q47034)    | Espoo       | city (wd:Q515) | Helsinki metropolitan area (wd:Q673425)      |
| Porvoo (wd:Q193367)  | Porvoo      | city (wd:Q515) | Porvoo sub-region (wd:Q1191744)              |
| Porvoo (wd:Q193367)  | Porvoo      | city (wd:Q515) | Uusimaa (wd:Q5711)                           |
| Stockholm (wd:Q1754) | Stockholm   | city (wd:Q515) |                                              |
| Turku (wd:Q38511)    | Turku       | city (wd:Q515) |                                              |
| Vaasa (wd:Q125080)   | Vaasa       | city (wd:Q515) | Swedish-speaking Ostrobothnia (wd:Q10685649) |
| Vantaa (wd:Q127623)  | Vantaa      | city (wd:Q515) | Helsinki capital region (wd:Q18691387)       |
| Vantaa (wd:Q127623)  | Vantaa      | city (wd:Q515) | Helsinki metropolitan area (wd:Q673425)      |

The distinct places where Swedish is an official language, along with their labels, the unique instances they belong to, and the unique entities they are part of, ordered alphabetically by the place label, are:
- Espoo (city, part of Helsinki capital region and Helsinki metropolitan area)
- Porvoo (city, part of Porvoo sub-region and Uusimaa)
- Stockholm (city)
- Turku (city)
- Vaasa (city, part of Swedish-speaking Ostrobothnia)
- Vantaa (city, part of Helsinki capital region and Helsinki metropolitan area)

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the distinct places where the official language is Swedish, along with their labels, the unique instances they belong to (if available), and the unique entities they are part of (if available)? Order results alphabetically by place label.

[Assistant]
To answer this question, we need to identify the entities and properties related to places where Swedish is an official language. We also need to retrieve the labels of these places, the unique instances they belong to, and the unique entities they are part of. Finally, we need to order the results alphabetically by the place label.

Let's start by searching for the entity representing the Swedish language.

[Tool]
Top 10 entity alternatives:
1. Swedish, also known as Swedish language, swed1254, swe, Svenska, sv (wd:Q9027): North Germanic language spoken in Sweden and Finland
2. Swedish language (wd:L616488-S1)
3. Swedish (language) (wd:L743847-S1)
4. Swedish (language) (wd:L612724-S1)
5. Swedish Sign Language, also known as swl, SSL, STS (wd:Q36558): sign language
6. Swedish Language Council (wd:Q3500437): Swedish government agency for language policy
7. Thesaurus:penis (Swedish language) (wd:Q101144592)
8. teaching of Swedish, also known as Swedish language teaching, Swedish language instruction (wd:Q10685751)
9. Swedish language family (wd:Q12646226): family of languages closely related to standard Swedish
10. dictionary of the Swedish language, also known as dictionary of Swedish, Swedish language dictionary, Swedish dictionary (wd:Q55623753): language version of dictionary

[Assistant] The top result for the Swedish language is `wd:Q9027`. Now, let's find the property that indicates the official language of a place.

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): language designated as official by this item, language used
2. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): label for the items in their official language  or their original language, name
3. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): language status identifier by Ethnologue.com using EGIDS scale
4. language regulatory body, also known as language authority, regulatory body (wd:P1018 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): regulatory body of a language
5. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): language(s) that a person or a people speaks, writes or signs, including the native language(s)
6. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): language or languages a person has learned from early childhood, languages spoken, written or signed
7. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): language widely used (spoken or written) in this place or at this event or organisation
8. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
9. programmed in, also known as language, programming language, written in (wd:P277 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): the programming language(s) in which the software is developed
10. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): language in which the writer has written their work, languages spoken, written or signed

[Assistant]
The property for "official language" is `wd:P37`. Now, we can construct a SPARQL query to find the places where Swedish (`wd:Q9027`) is an official language. We will also retrieve the labels of these places, the unique instances they belong to, and the unique entities they are part of. Finally, we will order the results alphabetically by the place label.

Let's start with a basic query to find the places where Swedish is an official language and their labels.

[Tool]
Got 279 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?place                                     | ?placeLabel                 |
| ------------------------------------------ | --------------------------- |
| Åbo Akademi University (wd:Q917874)        | Åbo Akademi University      |
| Åbo Nation (wd:Q4356338)                   | Åbo Nation                  |
| Åbo Svenska Teater (wd:Q118582926)         | Åbo Svenska Teater          |
| Åggelby svenska samskola (wd:Q106255235)   | Åggelby svenska samskola    |
| Akademiska Damkören Lyran (wd:Q10403936)   | Akademiska Damkören Lyran   |
| ...                                        | ...                         |
| Vilhelmina Municipality (wd:Q515861)       | Vilhelmina Municipality     |
| Vörå (wd:Q2156306)                         | Vörå                        |
| Vörå Upper Secondary School (wd:Q10718963) | Vörå Upper Secondary School |
| Wasa Theater (wd:Q3431686)                 | Wasa Theater                |
| Yrkeshögskolan Sydväst (wd:Q11903078)      | Yrkeshögskolan Sydväst      |

[Assistant]
The initial query returns the places where Swedish is an official language along with their labels. However, it includes a mix of places, organizations, and institutions. To refine the query, we need to filter out only the places (e.g., cities, municipalities, regions).

We can use the `wdt:P31` property to filter for instances of specific types, such as cities, municipalities, or regions. Let's search for the entities representing these types of places.

First, let's search for the entity representing "city" or "municipality".

[Tool]
Top 10 entity alternatives:
1. city, also known as cities (wd:Q515): large human settlement
2. Manchester City F.C., also known as The Sky Blues, City, The Citizens, The Blues, Sky Blues (wd:Q50602): association football club in Manchester, England
3. Leicester City F.C., also known as The Foxes, Leicester Fosse Football Club, Leicester Fosse FC, Leicester Fosse, Leicester City (wd:Q19481): association football club in Leicester, England
4. Swansea City A.F.C., also known as Swansea City Association Football Club, The Swans, The Jacks, Swansea City AFC, Swansea City (wd:Q18659): association football club in Swansea, Wales
5. Stoke City F.C., also known as City, SCFC, Stoke, Stoke City, Stoke City FC (wd:Q18736): association football club in Stoke-on-Trent, England
6. Birmingham City F.C., also known as BCFC, City, Blues, Birmingham City Football Club, Birmingham City (wd:Q19444): association football club in Birmingham, England
7. Norwich City F.C., also known as Norwich City FC, The Canaries, Norwich City Football Club, Norwich City, Norwich (wd:Q18721): association football club in Norwich, England
8. Cardiff City F.C., also known as Cardiff, The Bluebirds, City, CCFC, Cardiff City Football Club (wd:Q18662): association football club in Cardiff, Wales
9. Hull City A.F.C., also known as City, HCAFC, Hull, Hull City, Hull City AFC (wd:Q19477): association football club in Hull, England
10. Coventry City F.C., also known as Coventry City FC, Sky Blues, Coventry City Football Club, Coventry City, Coventry (wd:Q19580): association football club in Coventry, England

[Assistant] The top result for "city" is `wd:Q515`. Now, let's search for the entity representing "municipality" to include both cities and municipalities in our query.

[Tool]
Top 10 entity alternatives:
1. municipality, also known as municipalities (wd:Q15284): administrative division having corporate status and usually powers of self-government or jurisdiction
2. direct-administered municipality, also known as direct-administrated municipality, direct-controlled municipality, municipality, province-level municipality (wd:Q1208802): province-level subdivision in the People's Republic of China
3. municipality of the Philippines, also known as Philippine town, Philippine municipality, municipality (wd:Q24764): administrative division in Philippine provinces
4. municipality of Georgia, also known as municipality (wd:Q2655841): subdivision of Georgia, consisting of a settlement or a group of settlements
5. county town, also known as municipality (wd:Q1357964): county's administrative centre in the United Kingdom or Ireland
6. municipality of Albania, also known as municipality (wd:Q768307): administrative division of Albania
7. término municipal, also known as municipal area council, municipal area, municipal territory, municipality, municipal term (wd:Q55843): territory of a municipality of Spain or Portugal, on which the jurisdiction of a town hall extends
8. municipality of Macau, also known as concelho of Macau, municipality (wd:Q17361234): historic administrative subdivision of Macau
9. municipality, also known as municipality of Quebec (wd:Q27676428): type of municipality in Quebec; these are municipalities that only have "municipality" in their status
10. Sundarharaincha, also known as Municipality (wd:Q75947148): municipality in eastern Nepal lies in province 1

[Assistant]
The top result for "municipality" is `wd:Q15284`. Now, we can refine our SPARQL query to include only places that are instances of either a city (`wd:Q515`) or a municipality (`wd:Q15284`). We will also retrieve the unique instances they belong to (if available) and the unique entities they are part of (if available). Finally, we will order the results alphabetically by the place label.

Let's construct and execute this refined query.

[Tool]
Got 9 rows and 4 columns:
| ?place               | ?placeLabel | ?instanceOf    | ?partOf                                      |
| -------------------- | ----------- | -------------- | -------------------------------------------- |
| Espoo (wd:Q47034)    | Espoo       | city (wd:Q515) | Helsinki capital region (wd:Q18691387)       |
| Espoo (wd:Q47034)    | Espoo       | city (wd:Q515) | Helsinki metropolitan area (wd:Q673425)      |
| Porvoo (wd:Q193367)  | Porvoo      | city (wd:Q515) | Porvoo sub-region (wd:Q1191744)              |
| Porvoo (wd:Q193367)  | Porvoo      | city (wd:Q515) | Uusimaa (wd:Q5711)                           |
| Stockholm (wd:Q1754) | Stockholm   | city (wd:Q515) |                                              |
| Turku (wd:Q38511)    | Turku       | city (wd:Q515) |                                              |
| Vaasa (wd:Q125080)   | Vaasa       | city (wd:Q515) | Swedish-speaking Ostrobothnia (wd:Q10685649) |
| Vantaa (wd:Q127623)  | Vantaa      | city (wd:Q515) | Helsinki capital region (wd:Q18691387)       |
| Vantaa (wd:Q127623)  | Vantaa      | city (wd:Q515) | Helsinki metropolitan area (wd:Q673425)      |

[Assistant]
The refined query has returned the distinct places where Swedish is an official language, along with their labels, the unique instances they belong to, and the unique entities they are part of. The results are ordered alphabetically by the place label.

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?place ?placeLabel ?instanceOf ?partOf WHERE {
  ?place wdt:P37 wd:Q9027 .
  ?place wdt:P31 ?instanceOf .
  ?place rdfs:label ?placeLabel .
  OPTIONAL {
    ?place wdt:P361 ?partOf .
    ?partOf rdfs:label ?partOfLabel .
    FILTER(LANG(?partOfLabel) = 'en')
  }
  FILTER(?instanceOf = wd:Q515 || ?instanceOf = wd:Q15284)
  FILTER(LANG(?placeLabel) = 'en')
} ORDER BY ?placeLabel
```

Answer:
- Espoo (city, part of Helsinki capital region and Helsinki metropolitan area)
- Porvoo (city, part of Porvoo sub-region and Uusimaa)
- Stockholm (city)
- Turku (city)
- Vaasa (city, part of Swedish-speaking Ostrobothnia)
- Vantaa (city, part of Helsinki capital region and Helsinki metropolitan area)

These are the distinct places where Swedish is an official language, along with their labels, the unique instances they belong to, and the unique entities they are part of, ordered alphabetically by the place label.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX schema: <http://schema.org/>
SELECT ?property ( COUNT( ?property ) AS ?count ) WHERE {
  {
    ?item wdt:P31 wd:Q40231 .
  } UNION {
    ?item wdt:P279 wd:Q40231 .
  }
  ?item ?property ?value .
  FILTER ( ?property NOT IN ( schema:name , rdfs:label , skos:prefLabel , schema:description ) )
}
GROUP BY ?property
ORDER BY DESC ( ?count )

Got 442 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property                                   | ?count |
| ------------------------------------------- | ------ |
| instance of (wdt:P31)                       | 24423  |
| instance of (p:P31)                         | 24423  |
| rdf:type                                    | 24050  |
| country (p:P17)                             | 20278  |
| country (wdt:P17)                           | 20274  |
| ...                                         | ...    |
| short name (p:P1813)                        | 1      |
| STW Thesaurus for Economics ID (wdtn:P3911) | 1      |
| operating area (wdt:P2541)                  | 1      |
| legislative body (p:P194)                   | 1      |
| author name string (p:P2093)                | 1      |

The properties used in claims related to items that are public elections, along with the count of how many times each property is used, are as follows: instance of (wdt:P31) - 24423, country (wdt:P17) - 20274, rdf:type - 24050, and others.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which properties are used in claims related to items that are public elections? Include a count of the number of times it was used.

[Assistant] To answer this question, we need to identify the items that are public elections and then find out which properties are used in claims related to these items. We also need to count the number of times each property is used. Let's start by searching for the entity "public election" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. public election, also known as elections, election (wd:Q40231): process by which a population chooses the holder of a public office
2. Public election committee (wd:Q127273596)
3. Public Offices Election Act (wd:Q11392186)
4. Public Official Election Act (wd:Q12592014): South Korean law
5. Election publication praised (wd:Q95492900)
6. 2009 New York City Public Advocate election, also known as 2009 NYC Public Advocate election, New York City Public Advocate election, 2009 (wd:Q7013284)
7. 2017 New York City Public Advocate election, also known as 2017 NYC Public Advocate election, New York City Public Advocate election, 2017 (wd:Q43078961)
8. 2021 New York City Public Advocate election, also known as 2021 NYC Public Advocate election (wd:Q106651975)
9. 2013 New York City Public Advocate election, also known as New York City Public Advocate election, 2013, 2013 NYC Public Advocate election (wd:Q17091644)
10. 2019 New York City Public Advocate election, also known as 2019 NYC Public Advocate election (wd:Q85732015)

[Assistant] The top result, "public election" (wd:Q40231), seems to be the most relevant. Now, let's list the triples where this entity is the subject to understand what properties are commonly associated with it.

[Tool]
Got 790 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                                       | object                                                                        |
| --------------------------- | ---------------------------------------------- | ----------------------------------------------------------------------------- |
| public election (wd:Q40231) | Commons category (wdt:P373)                    | Elections                                                                     |
| public election (wd:Q40231) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/Election%20MG%203455.JPG> |
| public election (wd:Q40231) | part of (wdt:P361)                             | politics (wd:Q7163)                                                           |
| public election (wd:Q40231) | subclass of (wdt:P279)                         | voting (wd:Q189760)                                                           |
| public election (wd:Q40231) | described by source (wdt:P1343)                | Brockhaus and Efron Encyclopedic Dictionary (wd:Q602358)                      |
| public election (wd:Q40231) | on focus list of Wikimedia project (wdt:P5008) | wd:Q6173448                                                                   |
| public election (wd:Q40231) | different from (wdt:P1889)                     | corporate election (wd:Q5172455)                                              |
| public election (wd:Q40231) | topic's main category (wdt:P910)               | wd:Q4273219                                                                   |
| public election (wd:Q40231) | pronunciation audio (wdt:P443)                 | <http://commons.wikimedia.org/wiki/Special:FilePath/De-Wahl.ogg>              |
| public election (wd:Q40231) | Commons gallery (wdt:P935)                     | Election                                                                      |
| ...                         | ...                                            | ...                                                                           |

[Assistant]
From the list of triples, we can see some properties that are directly associated with the entity "public election" (wd:Q40231). However, to get a comprehensive list of properties used in claims related to items that are public elections, we need to query for all items that are instances or subclasses of "public election" and then count the properties used in their claims.

Let's start by identifying all items that are instances or subclasses of "public election" (wd:Q40231).

### Step 1: Identify all items that are instances or subclasses of "public election"
We will use the `wdt:P31` (instance of) and `wdt:P279` (subclass of) properties to find these items.

### Step 2: Count the properties used in claims related to these items
We will then count the occurrences of each property used in claims related to these items.

Let's execute the SPARQL query to achieve this.

```sparql
SELECT ?property (COUNT(?property) AS ?count)
WHERE {
  {
    ?item wdt:P31 wd:Q40231 .
  } UNION {
    ?item wdt:P279 wd:Q40231 .
  }
  ?item ?property ?value .
}
GROUP BY ?property
ORDER BY DESC(?count)
```

This query will give us the properties used in claims related to items that are public elections, along with the count of how many times each property is used.

Let's execute this query.

[Tool]
Got 446 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property                                   | ?count |
| ------------------------------------------- | ------ |
| schema:name                                 | 38798  |
| rdfs:label                                  | 38798  |
| skos:prefLabel                              | 38798  |
| schema:description                          | 29478  |
| instance of (wdt:P31)                       | 24423  |
| ...                                         | ...    |
| short name (p:P1813)                        | 1      |
| STW Thesaurus for Economics ID (wdtn:P3911) | 1      |
| operating area (wdt:P2541)                  | 1      |
| legislative body (p:P194)                   | 1      |
| author name string (p:P2093)                | 1      |

[Assistant]
The SPARQL query has returned the properties used in claims related to items that are public elections, along with the count of how many times each property is used. The results show that the most frequently used properties are `schema:name`, `rdfs:label`, `skos:prefLabel`, and `schema:description`.

However, these properties are often used for metadata and labeling purposes rather than for specific claims about the elections themselves. To get a more meaningful list of properties, we should filter out these common metadata properties and focus on properties that are more specific to the domain of elections.

Let's refine the query to exclude common metadata properties and focus on more specific properties.

### Step 3: Refine the query to exclude common metadata properties
We will exclude properties like `schema:name`, `rdfs:label`, `skos:prefLabel`, and `schema:description` from the results.

Here is the refined SPARQL query:

```sparql
SELECT ?property (COUNT(?property) AS ?count)
WHERE {
  {
    ?item wdt:P31 wd:Q40231 .
  } UNION {
    ?item wdt:P279 wd:Q40231 .
  }
  ?item ?property ?value .
  FILTER(?property NOT IN (schema:name, rdfs:label, skos:prefLabel, schema:description))
}
GROUP BY ?property
ORDER BY DESC(?count)
```

Let's execute this refined query.

[Tool]
Got 442 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property                                   | ?count |
| ------------------------------------------- | ------ |
| instance of (wdt:P31)                       | 24423  |
| instance of (p:P31)                         | 24423  |
| rdf:type                                    | 24050  |
| country (p:P17)                             | 20278  |
| country (wdt:P17)                           | 20274  |
| ...                                         | ...    |
| short name (p:P1813)                        | 1      |
| STW Thesaurus for Economics ID (wdtn:P3911) | 1      |
| operating area (wdt:P2541)                  | 1      |
| legislative body (p:P194)                   | 1      |
| author name string (p:P2093)                | 1      |

[Assistant]
The refined SPARQL query has returned a list of properties used in claims related to items that are public elections, excluding common metadata properties. The most frequently used properties are `instance of (wdt:P31)`, `country (wdt:P17)`, and `rdf:type`.

These properties provide more specific information about the elections, such as the type of election and the country in which they take place. The results also include other properties that are less common but still relevant to the domain of elections.

### Final Answer
The properties used in claims related to items that are public elections, along with the count of how many times each property is used, are as follows:

```sparql
SELECT ?property (COUNT(?property) AS ?count)
WHERE {
  {
    ?item wdt:P31 wd:Q40231 .
  } UNION {
    ?item wdt:P279 wd:Q40231 .
  }
  ?item ?property ?value .
  FILTER(?property NOT IN (schema:name, rdfs:label, skos:prefLabel, schema:description))
}
GROUP BY ?property
ORDER BY DESC(?count)
```

This query provides a comprehensive list of properties and their usage counts, focusing on properties that are more specific to the domain of public elections.

Let's finalize the answer.

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT ?year ?studentCount WHERE {
  wd:Q317032 p:P2196 ?statement .
  ?statement ps:P2196 ?studentCount .
  ?statement pq:P585 ?year .
}
ORDER BY ?year

The number of students at the University of Düsseldorf (with ROR ID "024z2rq82") for each year is as follows:

| Year       | Number of Students |
|------------|--------------------|
| 1998       | 23,997             |
| 1999       | 24,789             |
| 2000       | 24,868             |
| 2001       | 25,537             |
| 2002       | 25,220             |
| ...        | ...                |
| 2018       | 36,571             |
| 2019       | 37,540             |
| 2019       | 37,473             |
| 2020       | 36,070             |
| 2021       | 33,942             |

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many students did the educational organization with the Research Organization Registry (ROR) ID "024z2rq82" have each year? Please include a count for each year (if available), and order results by year.

[Assistant]
To answer this question, we need to identify the educational organization with the ROR ID "024z2rq82" and then find the number of students it had each year. We'll start by searching for the entity with the ROR ID.

Let's search for the entity with the ROR ID "024z2rq82".

[Tool] No entity items found

[Assistant]
It seems that there is no entity in Wikidata with the ROR ID "024z2rq82". This could mean that the organization is not represented in Wikidata, or the ROR ID is not linked to the Wikidata entity.

Since the direct search did not yield any results, let's try to find the property that might link an organization to its ROR ID. We can then use this property to find the organization.

Let's search for the property that links an organization to its ROR ID.

[Tool]
Top 10 property alternatives:
1. ROR ID, also known as Research Organization Registry ID, ror.org ID (wd:P6782 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for the Research Organization Registry
2. Relations Ontology ID, also known as RO ID, Relation Ontology ID (wd:P3590 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): ID in the Relations Ontology
3. Rijksmuseum Research Library authority ID, also known as RRL ID (wd:P7444 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): authority control identifier for the Rijksmuseum Research Library
4. RBU person ID, also known as RBU ID (wd:P6387 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a person at the Russian Biathlon Union site
5. Online Coins of the Roman Empire ID, also known as OCRE ID, Roman Imperial Coinage ID, RIC ID, RIC coin ID, OCRE coin ID (wd:P9645 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier of a coin in the Online Coins of the Roman Empire pla...the Roman Imperial Coinage (RIC) series published by Spink & Son
6. Research Resource Identifier, also known as RRID, SciCrunch identifier (wd:P9712 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier in the SciCrunch database of research resources
7. Australian Women's Register ID, also known as AWR ID, womenaustralia.info (wd:P4186 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a person or organisation in the Australian Women's Register
8. Channel One Russia show ID, also known as 1tv.ru ID, Channel One Russia ID, COR ID (wd:P10170 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier of TV program for Channel One Russia
9. French national research structure ID, also known as French national research structure identifier, RNSR ID, national research structure identifier (France) (wd:P3016 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier in the French national research structure repertory
10. Russian Academy of Sciences person ID, also known as RAS ID, Russian Academy of Sciences ID (wd:P10133 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): identifier for a member of the Russian Academy of Sciences

[Assistant]
The top result for the property search is "ROR ID" (wd:P6782). This property is used to link an organization to its ROR ID. Let's use this property to find the entity with the ROR ID "024z2rq82".

We will construct a SPARQL query to find the entity with the ROR ID "024z2rq82" and then check if it has any information about the number of students per year.

Let's execute the following SPARQL query:

```sparql
SELECT ?organization WHERE {
  ?organization wdt:P6782 "024z2rq82" .
}
```

This query will help us identify the organization with the specified ROR ID.

[Tool]
Got 1 row and 1 column:
| ?organization                         |
| ------------------------------------- |
| University of Düsseldorf (wd:Q317032) |

[Assistant]
The organization with the ROR ID "024z2rq82" is the University of Düsseldorf (wd:Q317032).

Next, we need to find the number of students enrolled at the University of Düsseldorf each year. We will look for a property that represents the number of students and then construct a query to get the count for each year.

Let's search for the property that represents the number of students.

[Tool]
Top 10 property alternatives:
1. count of students, also known as count of pupils, count of students, enrollment, number of pupils, number of pupils or students (wd:P2196 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): number of pupils or students of any type in an educational organ...evious years normal rank (not deprecated rank). Don't overwrite.
2. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): notable student(s) of the subject individual, significant person
3. number of out-of-school children (wd:P2573 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): number of out-of-school children reported for a place
4. number of teachers, also known as faculty count (wd:P10610 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): number of teachers at an educational facility
5. school class, also known as class, cohort, grade, school cohort, stage (wd:P7174 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): (qualifier) class of a given year/time period to which the person belonged in an educational institution
6. number of children, also known as children, children (number), how many children, issue, kids (wd:P1971 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): number of children of the person, animal, or character
7. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): educational institution attended by subject, affiliation
8. student retention rate (wd:P11698 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): proportion of first-year students at the educational institution who return for their second year
9. number of participants, also known as number of competitors, number of teams, participant count, participants, qty participants (wd:P1132 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): number of participants of an event, e.g. people or groups of people that take part in the event (NO units), quantity
10. educational stage, also known as student classification (wd:P7374 as psv/p/wdtn/prv/ps/prn/psn/pq/wdt/pqn/pr/pqv): educational stage of a specific school; qualifier of "educated at" (P69): the education stage of someone's attendance of school

[Assistant]
The top result for the property search is "count of students" (wd:P2196), which represents the number of students or pupils in an educational organization.

Now, we will construct a SPARQL query to find the number of students at the University of Düsseldorf (wd:Q317032) for each year. We will also order the results by year.

Let's execute the following SPARQL query:

```sparql
SELECT ?year ?studentCount WHERE {
  wd:Q317032 p:P2196 ?statement .
  ?statement ps:P2196 ?studentCount .
  ?statement pq:P585 ?year .
}
ORDER BY ?year
```

This query will retrieve the number of students for each year and order the results by year.

[Tool]
Got 31 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?year                | ?studentCount |
| -------------------- | ------------- |
| 1998-01-01T00:00:00Z | 23997         |
| 1999-01-01T00:00:00Z | 24789         |
| 2000-01-01T00:00:00Z | 24868         |
| 2001-01-01T00:00:00Z | 25537         |
| 2002-01-01T00:00:00Z | 25220         |
| ...                  | ...           |
| 2018-01-01T00:00:00Z | 36571         |
| 2019-01-01T00:00:00Z | 37540         |
| 2019-01-01T00:00:00Z | 37473         |
| 2020-01-01T00:00:00Z | 36070         |
| 2021-01-01T00:00:00Z | 33942         |

[Assistant]
The SPARQL query has successfully retrieved the number of students at the University of Düsseldorf (wd:Q317032) for each year, ordered by year. Here are the results:

| Year       | Number of Students |
|------------|--------------------|
| 1998       | 23,997             |
| 1999       | 24,789             |
| 2000       | 24,868             |
| 2001       | 25,537             |
| 2002       | 25,220             |
| ...        | ...                |
| 2018       | 36,571             |
| 2019       | 37,540             |
| 2019       | 37,473             |
| 2020       | 36,070             |
| 2021       | 33,942             |

Note that there are two entries for the year 2019, which might indicate different data points or revisions. However, the query provides the required information.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?year ?studentCount WHERE {
  wd:Q317032 p:P2196 ?statement .
  ?statement ps:P2196 ?studentCount .
  ?statement pq:P585 ?year .
}
ORDER BY ?year
```

Answer: The number of students at the University of Düsseldorf (with ROR ID "024z2rq82") for each year is as follows:

| Year       | Number of Students |
|------------|--------------------|
| 1998       | 23,997             |
| 1999       | 24,789             |
| 2000       | 24,868             |
| 2001       | 25,537             |
| 2002       | 25,220             |
| ...        | ...                |
| 2018       | 36,571             |
| 2019       | 37,540             |
| 2019       | 37,473             |
| 2020       | 36,070             |
| 2021       | 33,942             |

[Tool] Stopped generation process